Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T22:05:20.500552Z
Paper Citation Record · LEDGER
As of 17 August 2026, this Paper Citation Record lists 100 of 155 outbound references and 2 inbound Pith citation observations for arXiv:2505.08834.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T22:05:20.500552Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T16:18:01.007594Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T09:26:01.650238Z
100 of 155 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 66fc54a0-1ee3-4b98-abc0-527ba18f2f60 · outbound
Crowd Scene Analysis using Deep Learning Techniques Elliott, S
Reference 1
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Observation b4ef93cc-9e0e-4730-9743-bac12898d54d · outbound
Crowd Scene Analysis using Deep Learning Techniques User, Physical, Virtual or Hybrid Events - Which Approach Is Best? — Think Global Forum — thinkglobalforum.org
Reference 2
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Observation 5d20947a-c36e-4a1e-91ea-72c31fefd7f5 · outbound
Crowd Scene Analysis using Deep Learning Techniques Physical Meetings: What Works and What Doesn’t — openaudience.com
Reference 3
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Observation cd2a4917-0b2e-4e19-a599-bd5c876df913 · outbound
Crowd Scene Analysis using Deep Learning Techniques Visual crowd analysis: Open research problems,
Reference 4
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Observation 44f95ee5-47b8-4e9f-a0af-c67afad2aca0 · outbound
Crowd Scene Analysis using Deep Learning Techniques Meel, People Counting System: How To Make Your Own in Less Than 10 Minutes - viso.ai — viso.ai
Reference 5
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Observation 6afb67eb-351a-445d-bc1b-6caf3fefc55c · outbound
Crowd Scene Analysis using Deep Learning Techniques Crowd Anomaly Detection in Video Frames Using Fine- Tuned AlexNet Model,
Reference 6
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Observation 9c55b1b1-7f79-4106-beb9-719f380ad296 · outbound
Crowd Scene Analysis using Deep Learning Techniques Multi-source multi-scale counting in extremely dense crowd images,
Reference 7
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Observation 8dc06320-8ca8-4907-93f0-470ba75b54f9 · outbound
Crowd Scene Analysis using Deep Learning Techniques Cross-scene crowd counting via deep convolutional neural networks,
Reference 8
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Observation fabb7774-9520-48e2-b547-ca032eeea325 · outbound
Crowd Scene Analysis using Deep Learning Techniques Learning to count objects in images,
Reference 9
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Observation b224dde7-dd1d-46d4-86fc-58aebd0d2c73 · outbound
Crowd Scene Analysis using Deep Learning Techniques Fully Convolutional Crowd Counting On Highly Congested Scenes
Reference 10
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Observation a9a5897f-a7ae-4eaa-8ad2-01ba7697dda7 · outbound
Crowd Scene Analysis using Deep Learning Techniques Crowdnet: A deep convolutional network for dense crowd counting,
Reference 11
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Observation 0e1213ff-657b-4159-bb4e-b467f2afbe10 · outbound
Crowd Scene Analysis using Deep Learning Techniques Density-aware person detection and tracking in crowds,
Reference 12
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Observation 8a48965b-cac3-493f-a582-c20831c0c357 · outbound
Crowd Scene Analysis using Deep Learning Techniques Single-image crowd counting via multi-column convolutional neural network,
Reference 13
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Observation 8d56a3a8-c0f0-4345-abc2-9f48dea17ce8 · outbound
Crowd Scene Analysis using Deep Learning Techniques Learning to detect violent videos using convolutional long short- term memory,
Reference 14
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Observation de1322ab-e2b2-48b9-ae8e-3ef25d0845ae · outbound
Crowd Scene Analysis using Deep Learning Techniques Bidirectional convolutional lstm for the detection of violence in videos,
Reference 15
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Observation aefe4e63-fd98-4ace-8499-c5825a607143 · outbound
Crowd Scene Analysis using Deep Learning Techniques Unified crowd segmentation,
Reference 16
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Observation 10772b34-3138-4379-8648-1aa88cbb6af1 · outbound
Crowd Scene Analysis using Deep Learning Techniques Granular-based dense crowd density estimation,
Reference 17
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Observation e1a28d65-9f8c-49fd-a23d-73ed02e00859 · outbound
Crowd Scene Analysis using Deep Learning Techniques CNN-based Density Estimation and Crowd Counting: A Survey
Reference 18
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Observation aa34c572-8e17-448f-a691-758746cb054f · outbound
Crowd Scene Analysis using Deep Learning Techniques An Introduction to Convolutional Neural Networks
Reference 19
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Observation 860d7934-3660-4eee-bdbc-7290bd53b0f9 · outbound
Crowd Scene Analysis using Deep Learning Techniques Fully convolutional networks for semantic segmentation,
Reference 20
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Observation c719d82e-851c-40b9-ae54-7db200cea24a · outbound
Crowd Scene Analysis using Deep Learning Techniques Generative adversarial nets,
Reference 21
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Observation a84e9388-c592-4317-b877-d69960270e86 · outbound
Crowd Scene Analysis using Deep Learning Techniques Generative adversarial networks: An overview,
Reference 22
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Observation d51b74f0-3a0b-4d86-b94f-06decc6f00e9 · outbound
Crowd Scene Analysis using Deep Learning Techniques Attention mechanisms in computer vision: A survey,
Reference 23
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Observation 7f42accc-debe-4ca3-b0c9-78f661a50d64 · outbound
Crowd Scene Analysis using Deep Learning Techniques A survey of the recent architectures of deep convolutional neural networks,
Reference 24
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Observation 4b708c83-ae4e-4802-9f80-c2ae4f6cd094 · outbound
Crowd Scene Analysis using Deep Learning Techniques A survey of recent advances in cnn-based single image crowd counting and density estimation,
Reference 25
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Observation 1173e8ae-a1f2-4ecf-866a-422c26fae05c · outbound
Crowd Scene Analysis using Deep Learning Techniques Revisiting crowd counting: State-of-the-art, trends, and future perspectives,
Reference 26
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Observation 4ce13f9c-b5ac-4b9c-b50a-ede6e2b22c66 · outbound
Crowd Scene Analysis using Deep Learning Techniques Analysis of various optimizers on deep convolutional neural network model in the application of hyperspectral remote sensing image classification,
Reference 27
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Observation 05b0ffbe-b84b-4dcf-a2c2-1c8d5d75854d · outbound
Crowd Scene Analysis using Deep Learning Techniques Novel sensitive nanocoatings based on SWCNT composites for advanced fiber optic chemo-sensors,
Reference 28
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Observation e89fa284-b72e-4f5b-b1ce-09bccece51ef · outbound
Crowd Scene Analysis using Deep Learning Techniques Resnetcrowd: A residual deep learning architecture for crowd counting, violent behaviour detection and crowd density level classification,
Reference 29
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Observation 3e4517df-b926-414d-986c-070cee2b0dee · outbound
Crowd Scene Analysis using Deep Learning Techniques Improving the Learning of Multi-column Convolutional Neural Network for Crowd Counting
Reference 30
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Observation 0ffb80d5-132d-485e-828d-8d66f8cae872 · outbound
Crowd Scene Analysis using Deep Learning Techniques Multi-scale convolutional neural networks for crowd counting,
Reference 31
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Observation 6c2cc2f5-b1b1-4eac-aaa6-d95acfd8ed18 · outbound
Crowd Scene Analysis using Deep Learning Techniques Rethinking counting and localization in crowds: A purely point-based framework,
Reference 32
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Observation e528ce64-0339-4d4c-92d8-2b0acbb682cf · outbound
Crowd Scene Analysis using Deep Learning Techniques Detection, tracking, and counting meets drones in crowds: A benchmark,
Reference 33
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Observation 164e8dfb-59e2-4717-9bd5-6471e4bc0f8f · outbound
Crowd Scene Analysis using Deep Learning Techniques Dense scale network for crowd counting,
Reference 34
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Observation ffe21c63-e57e-4137-a37b-49b4dd37404b · outbound
Crowd Scene Analysis using Deep Learning Techniques CRANet: cascade residual attention network for crowd counting,
Reference 35
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Observation f7e393ca-cc24-478d-be07-26980968ed77 · outbound
Crowd Scene Analysis using Deep Learning Techniques Spatiotemporal dilated convolution with uncertain matching for video-based crowd estimation,
Reference 36
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Observation fc4ba349-1d9c-42a9-b0fa-eebd0b9a25d3 · outbound
Crowd Scene Analysis using Deep Learning Techniques MSPNET: Multi-supervised parallel network for crowd counting,
Reference 37
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Observation 46eeb37c-adac-4b6e-b20f-60c0f9d2e518 · outbound
Crowd Scene Analysis using Deep Learning Techniques Dilated convolutional neural networks for understanding the highly congested scenes/Y . Li, X. Zhang, D. Chen,
Reference 38
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Observation 29bd96a5-d44b-4b10-a3b8-fd6b3f29715e · outbound
Crowd Scene Analysis using Deep Learning Techniques CLRNet: a cross locality relation network for crowd counting in videos,
Reference 39
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Observation f9327aa9-3c5f-418d-b422-8b6165b9e10d · outbound
Crowd Scene Analysis using Deep Learning Techniques Self-supervised domain adaptation in crowd counting,
Reference 40
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Observation 9efe50fb-ff38-435f-82e7-4d76a7de1827 · outbound
Crowd Scene Analysis using Deep Learning Techniques Tafnet: A three-stream adaptive fusion network for rgb-t crowd counting,
Reference 41
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Observation 6a0dbda6-10b4-4f1a-accb-0c08603563a6 · outbound
Crowd Scene Analysis using Deep Learning Techniques Boosting crowd counting via multifaceted attention,
Reference 42
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Observation 9e1626c4-d8eb-4965-bc01-37f8d3d1f7be · outbound
Crowd Scene Analysis using Deep Learning Techniques Nonlinear regression via deep negative correlation learning,
Reference 43
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Observation ede8364e-4c61-4055-940f-3c04514d4ac5 · outbound
Crowd Scene Analysis using Deep Learning Techniques Crowd counting with deep negative correlation learning,
Reference 44
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Observation 30bd61c0-f53a-48d8-a8c3-f4ac75175200 · outbound
Crowd Scene Analysis using Deep Learning Techniques CrowdCLIP: Unsupervised Crowd Counting via Vision-Language Model,
Reference 45
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Observation 3a53bb63-bb79-45a4-b1a4-14a0fab1edd4 · outbound
Crowd Scene Analysis using Deep Learning Techniques People count from the crowd using unsupervised learning technique from low resolution surveillance videos,
Reference 46
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Observation 4dde6267-bf60-4d3c-a57d-cc5bed599e0f · outbound
Crowd Scene Analysis using Deep Learning Techniques Almost unsupervised learning for dense crowd counting,
Reference 47
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Observation 3c3f7543-12c5-4b02-9dc2-f227a82b8f7f · outbound
Crowd Scene Analysis using Deep Learning Techniques Auto-Encoding Variational Bayes
Reference 48
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Observation 0fb13179-6442-4aa6-97bb-3489abd4a59a · outbound
Crowd Scene Analysis using Deep Learning Techniques CrowdFormer: Weakly-supervised crowd counting with improved generalizability,
Reference 49
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Observation 83e8a939-86e1-4053-b745-ef60487c07b6 · outbound
Crowd Scene Analysis using Deep Learning Techniques Transcrowd: weakly-supervised crowd counting with transformers,
Reference 50
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Crowd Scene Analysis using Deep Learning Techniques Exploiting unlabeled data in cnns by self- supervised learning to rank,
Reference 51
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Observation 6d0c6052-629e-487d-8525-438021d3cb40 · outbound
Crowd Scene Analysis using Deep Learning Techniques Self-Supervised Learning With Data- Efficient Supervised Fine-Tuning for Crowd Counting,
Reference 52
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Observation 4f75778b-ccfe-43b1-8a0b-f7436f95e8c9 · outbound
Crowd Scene Analysis using Deep Learning Techniques Unsupervised learning of visual representations by solving jigsaw puzzles,
Reference 53
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Observation 28d988c9-46ce-4091-9d16-0a6d39e8fb31 · outbound
Crowd Scene Analysis using Deep Learning Techniques Context encoders: Feature learning by inpainting,
Reference 54
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Crowd Scene Analysis using Deep Learning Techniques Colorization as a proxy task for visual understanding,
Reference 55
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Observation 1e83b6fe-3651-4d12-b43d-b3a293e95e8e · outbound
Crowd Scene Analysis using Deep Learning Techniques Learning deep event models for crowd anomaly detection,
Reference 56
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Crowd Scene Analysis using Deep Learning Techniques Unsupervised Representation Learning by Predicting Image Rotations
Reference 57
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Observation 055d2534-059d-44f8-80e1-ee1d56ed6778 · outbound
Crowd Scene Analysis using Deep Learning Techniques Context-aware crowd counting,
Reference 58
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Observation d50ed77a-d69a-4f3e-b638-9b3c65e6296e · outbound
Crowd Scene Analysis using Deep Learning Techniques Recent trends in crowd analysis: A review,
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Observation c6cc01ac-9a6e-4af5-b15b-aa982cef11b1 · outbound
Crowd Scene Analysis using Deep Learning Techniques Modeling Representation of Videos for Anomaly Detection using Deep Learning: A Review
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Observation 2ddcf8f3-cf45-4deb-8be4-0e2d63d5992a · outbound
Crowd Scene Analysis using Deep Learning Techniques Shape-based human detection and segmentation via hierarchical part- template matching,
Reference 61
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Observation 2d5f12b1-a3e8-4e21-bf87-0cc817e78d76 · outbound
Crowd Scene Analysis using Deep Learning Techniques Pedestrian detection via classification on riemannian manifolds,
Reference 62
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Observation 03c51c5f-e84d-443c-89be-0fd608a69f65 · outbound
Crowd Scene Analysis using Deep Learning Techniques Counting people by clustering person detector outputs,
Reference 63
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Crowd Scene Analysis using Deep Learning Techniques Object detection with discriminatively trained part-based models,
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Crowd Scene Analysis using Deep Learning Techniques Estimating the number of people in crowded scenes by mid based foreground segmentation and head-shoulder detection,
Reference 65
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Crowd Scene Analysis using Deep Learning Techniques Locate, size, and count: accurately resolving people in dense crowds via detection,
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Observation 639a95d6-9b3b-4572-a7e9-bea7598ba567 · outbound
Crowd Scene Analysis using Deep Learning Techniques Point in, box out: Beyond counting persons in crowds,
Reference 67
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Observation 9dcc4b38-b907-46be-b40c-1c765b031ec9 · outbound
Crowd Scene Analysis using Deep Learning Techniques A self-training approach for point-supervised object detection and counting in crowds,
Reference 68
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Crowd Scene Analysis using Deep Learning Techniques Count forest: Co-voting uncertain number of targets using random forest for crowd density estimation,
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Crowd Scene Analysis using Deep Learning Techniques A deeply-recursive convolutional network for crowd counting,
Reference 70
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Crowd Scene Analysis using Deep Learning Techniques Switching convolutional neural network for crowd counting,
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Crowd Scene Analysis using Deep Learning Techniques Multi-resolution attention convolutional neural network for crowd counting,
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Crowd Scene Analysis using Deep Learning Techniques Image crowd counting using convolutional neural network and markov random field,
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Crowd Scene Analysis using Deep Learning Techniques Csrnet: Dilated convolutional neural networks for understanding the highly congested scenes,
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Crowd Scene Analysis using Deep Learning Techniques Relational attention network for crowd counting,
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Crowd Scene Analysis using Deep Learning Techniques Cnn-based cascaded multi-task learning of high-level prior and density estimation for crowd counting,
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Crowd Scene Analysis using Deep Learning Techniques Dense crowd counting from still images with convolutional neural networks,
Reference 77
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Reference 78
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Crowd Scene Analysis using Deep Learning Techniques Mixture of Counting CNNs: Adaptive Integration of CNNs Specialized to Specific Appearance for Crowd Counting
Reference 79
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Crowd Scene Analysis using Deep Learning Techniques Violence detection in surveillance videos with deep network using transfer learning,
Reference 80
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Crowd Scene Analysis using Deep Learning Techniques Violence detection in videos based on fusing visual and audio information,
Reference 81
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Crowd Scene Analysis using Deep Learning Techniques Violence content classification using audio features,
Reference 82
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Crowd Scene Analysis using Deep Learning Techniques CASSANDRA: audio-video sensor fusion for aggression detection,
Reference 83
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Crowd Scene Analysis using Deep Learning Techniques Detecting violent scenes in movies by auditory and visual cues,
Reference 84
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Observation 953d21e3-d81b-4dc6-a598-f5b2ded71a43 · outbound
Crowd Scene Analysis using Deep Learning Techniques DOVE: Detection of movie violence using motion intensity analysis on skin and blood,
Reference 85
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Observation 945f3052-3d80-4c1d-b154-4e999364264a · outbound
Crowd Scene Analysis using Deep Learning Techniques A comprehensive review on vision-based violence detection in surveillance videos,
Reference 86
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Observation a052c3af-0a41-4b44-bbd3-2877fd9a27cb · outbound
Crowd Scene Analysis using Deep Learning Techniques Spatio-temporal anomaly detection in crowd movement using SIFT,
Reference 87
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Crowd Scene Analysis using Deep Learning Techniques Object tracking using SIFT features and mean shift,
Reference 88
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Crowd Scene Analysis using Deep Learning Techniques Speeded-up robust features (SURF),
Reference 89
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Crowd Scene Analysis using Deep Learning Techniques BRISK: Binary robust invariant scalable keypoints,
Reference 90
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Crowd Scene Analysis using Deep Learning Techniques ORB: An efficient alternative to SIFT or SURF,
Reference 91
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Observation c0c9db23-5290-44fa-b207-1fa72a154f4e · outbound
Crowd Scene Analysis using Deep Learning Techniques Evaluating bag-of-visual-words representations in scene classification,
Reference 92
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Observation adeb24a3-14ce-4d1f-adaf-c758bc4b0b05 · outbound
Crowd Scene Analysis using Deep Learning Techniques Violent flows: Real-time detection of violent crowd behavior,
Reference 93
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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 107bf90d-093f-49cc-916b-c8bf2b8e3dbf · outbound
Crowd Scene Analysis using Deep Learning Techniques Social mil: Interaction-aware for crowd anomaly detection,
Reference 94
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation a84a708c-49f1-4b99-83da-318ee52c6a10 · outbound
Crowd Scene Analysis using Deep Learning Techniques Application of deep learning for crowd anomaly detection from surveillance videos,
Reference 95
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 600f6a30-ad6d-4588-b347-27b650ab1dea · outbound
Crowd Scene Analysis using Deep Learning Techniques Anomaly and activity recognition using machine learning approach for video based surveillance,
Reference 96
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation acd8dcc6-bfa9-407b-a431-be735dc84e76 · outbound
Crowd Scene Analysis using Deep Learning Techniques Efficient anomaly detection in crowd videos using pre-trained 2D convolutional neural networks,
Reference 97
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b3dddcbb-a8f7-4276-916b-5cabcb54a070 · outbound
Crowd Scene Analysis using Deep Learning Techniques Self-supervised representation learning by rotation feature decoupling,
Reference 98
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 541e3a60-b3f8-4a25-8f1f-b20b318baaee · outbound
Crowd Scene Analysis using Deep Learning Techniques An automated deep learning based anomaly detection in pedestrian walkways for vulnerable road users safety,
Reference 99
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 1fbacfb2-5558-4612-88ee-34b9c29f2fd2 · outbound
Crowd Scene Analysis using Deep Learning Techniques Joint detection and recounting of abnormal events by learning deep generic knowledge,
Reference 100
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 22064291-e4ee-4486-a104-17e63440554e · inbound
Advancements in Crop Analysis through Deep Learning and Explainable AI Crowd Scene Analysis using Deep Learning Techniques
Reference 14
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4fa44990-ab13-45aa-bf7d-9d58e318b3e9 · inbound
Towards Automated Solar Panel Integrity: Hybrid Deep Feature Extraction for Advanced Surface Defect Identification Crowd Scene Analysis using Deep Learning Techniques
Reference 29
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.