Results 101 to 110 of about 5,507,676 (170)

Urban theft prediction via LLM-empowered spatiotemporal transformer. [PDF]

Sci Rep
Tang M, Wang J, Bu X, Zhang J, Luo P.
europepmc   +1 more source

Learn the interactions: Weakly supervised video anomaly detection with human-object interactions. [PDF]

PLoS One
Zhou M, Faizal Abdullah ERM, Sabri AQM, Rahardja S.   +3 more
europepmc   +1 more source

BAYESIAN EMPIRICAL LIKELIHOOD FOR ULTRA-HIGH DIMENSIONAL VARIABLE SELECTION WITH APPLICATION TO DRUG SENSITIVITY. [PDF]

Ann Appl Stat
Xu C, Lu Z, Cheng Y, Song Q, Zhao Y, Wang X.   +5 more
europepmc   +1 more source

Crime Prediction Using Twitter Sentiments and Crime Data

Informatica
G. Taiwo, Muhamad Saraee, Jimoh Fatai
semanticscholar   +1 more source

PoinCLIP-VAD: a hyperbolic cross-modal fusion framework for video anomaly detection. [PDF]

Sci Rep
Senapati DP, Pani SK, Baliarsingh SK, Dev PP, Somula R.   +4 more
europepmc   +1 more source

Learning Fine-Grained Video Anomaly Detection from Normal Videos. [PDF]

Sensors (Basel)
Wang R, Tamura Y, Yamamoto M.
europepmc   +1 more source

Rethinking criminal profiling through cognitive artificial intelligence. [PDF]

Front Artif Intell
Buele J, Miranda-Toapanta D, Rojas-Cañizares D.   +2 more
europepmc   +1 more source

Looking to Deceive: Voluntary Gaze Control Reduces the Discriminative Power of Eye-Movement-Based Concealed Information Testing. [PDF]

J Eye Mov Res
Milosavljević N, Panjevac M, Janković MM, Ković V.   +3 more
europepmc   +1 more source

Civilianized safety practitioners reduce crime and disorder: Evidence from a quasiexperimental evaluation in San Francisco. [PDF]

PNAS Nexus
Stuart F, Moore CL, Janulis P.
europepmc   +1 more source

A spatiotemporal deep learning framework for detecting unusual human activity in surveillance videos. [PDF]

PLoS One
Kumar M, Biswas M, Patel AK, Kumar A, Abhishek K, Shafeeq B M A.   +5 more
europepmc   +1 more source