Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Deep BiLSTM Attention Model for Spatial and Temporal Anomaly Detection in Video Surveillance. Retrieved May 24, 2026, from https://4ort.xyz/entity/deep-bilstm-attention-model-for-spatial-and-temporal-anomaly-detection-in-video-surveillance
MLA“Deep BiLSTM Attention Model for Spatial and Temporal Anomaly Detection in Video Surveillance.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/deep-bilstm-attention-model-for-spatial-and-temporal-anomaly-detection-in-video-surveillance.
BibTeX@misc{4ortxyz_deep-bilstm-attention-model-for-spatial-and-temporal-anomaly-detection-in-video-surveillance_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Deep BiLSTM Attention Model for Spatial and Temporal Anomaly Detection in Video Surveillance}}, year = {2026}, url = {https://4ort.xyz/entity/deep-bilstm-attention-model-for-spatial-and-temporal-anomaly-detection-in-video-surveillance}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Deep BiLSTM Attention Model for Spatial and Temporal Anomaly Detection in Video Surveillance — https://4ort.xyz/entity/deep-bilstm-attention-model-for-spatial-and-temporal-anomaly-detection-in-video-surveillance (retrieved 2026-05-24)
