Improved method for a pedestrian detection model based on YOLO by Yanfei LI, Chengyi DONG

“…The proposed method had superior performance in dense agricultural contexts while improving detection capabilities for pedestrian distribution patterns under complex farmland conditions, including variable lighting and mechanical occlusions. …”
Get full text

A Novel Semantic Driven Meta-Learning Model for Rare Attack Detection by Y. Annie Jerusha, S. P. Syed Ibrahim, Vijay Varadharajan

“…Our approach enhances intrusion detection by integrating an attention-based model for semantic feature extraction and the Simple Neural Attentive Meta-Learner (SNAIL) for rare attack class detection. …”
Get full text

Lightweight hybrid transformers-based dyslexia detection using cross-modality data by Abdul Rahaman Wahab Sait, Yazeed Alkhurayyif

“…Traditional dyslexia detection (DD) relies on lengthy, subjective, restricted behavioral evaluations and interviews. …”
Get full text

BiCA-LI: A Cross-Attention Multi-Task Deep Learning Model for Time Series Forecasting and Anomaly Detection in IDC Equipment by Zhongxing Sun, Yuhao Zhou, Zheng Gong, Cong Wen, Zhenyu Cai, Xi Zeng

“…The dual-encoder design, coupled with cross-modal attention fusion and gradient-aware loss optimization, enables robust joint modeling of heterogeneous temporal patterns. …”
Get full text

DAHD-YOLO: A New High Robustness and Real-Time Method for Smoking Detection by Jianfei Zhang, Chengwei Jiang

“…Recent advancements in AI technologies have driven the extensive adoption of deep learning architectures for recognizing human behavioral patterns. However, the existing smoking behavior detection models based on object detection still have problems, including poor accuracy and insufficient real-time performance. …”
Get full text

A Network Traffic Anomaly Classification Model Based on Self-Attention Mechanism and Convolutional Gated Recurrent Unit by Yulian Li, Yang Su

“…The detection of minority-class traffic (anomalous traffic) is crucial for network security. …”
Get full text

Enhanced APT detection with the improved KAN algorithm: capturing interdependencies for better accuracy by Weiwu Ren, Hewen Zhang, Yu Hong, Zhiwei Wang

“…Abstract In real-world network environments, advanced persistent threats (APTs) are characterized by their complexity and persistence. Existing APT detection methods often struggle to comprehensively capture the complex and dynamic network relationships and covert attack patterns involved in the attack process, and they also suffer from insufficient detection effectiveness. …”
Get full text

Graph neural network-based water contamination detection from community housing information by Raphael Anaadumba, Yigit Bozkurt, Connor Sullivan, Madhavi Pagare, Pradeep Kurup, Benyuan Liu, Mohammad Arif Ul Alam

“…Introduction: Detecting water contamination in community housing is crucial for protecting public health. …”
Get full text

Novel Approach in Vegetation Detection Using Multi-Scale Convolutional Neural Network by Fatema A. Albalooshi

“…This study explores the potential of a multi-scale convolutional neural network (MSCNN) design for object classification, specifically focusing on vegetation detection. The MSCNN is designed to integrate multi-scale feature extraction and attention mechanisms, enabling the model to capture both fine and coarse vegetation patterns effectively. …”
Get full text

Small object detection in side-scan sonar images based on SOCA-YOLO and image restoration by Xiaodong Cui, Jiale Zhang, Lingling Zhang, Qunfei Zhang, Jing Han

“…Furthermore, the model integrates the standardized CBAM (Convolutional Block Attention Module) attention mechanism, enabling adaptive focus on salient regions of small targets in sonar images, thereby significantly improving detection robustness in complex underwater environments. …”
Get full text

SLEEP-SAFE: Self-Supervised Learning for Estimating Electroencephalogram Patterns With Structural Analysis of Fatigue Evidence by Wonjun Ko, Jeongwon Choe, Jonggu Kang

Get full text

Synchronous Analysis of Speech Production and Lips Movement to Detect Parkinson’s Disease Using Deep Learning Methods by Cristian David Ríos-Urrego, Daniel Escobar-Grisales, Juan Rafael Orozco-Arroyave

Get full text

IRFNet: Cognitive-Inspired Iterative Refinement Fusion Network for Camouflaged Object Detection by Guohan Li, Jingxin Wang, Jianming Wei, Zhengyi Xu

“…Camouflaged Object Detection (COD) aims to identify objects that are intentionally concealed within their surroundings through appearance, texture, or pattern adaptations. …”
Get full text

A Deep Learning Method for Improving Community Multiscale Air Quality Forecast: Bias Correction, Event Detection, and Temporal Pattern Alignment by Ioannis Stergiou, Nektaria Traka, Dimitrios Melas, Efthimios Tagaris, Rafaella-Eleni P. Sotiropoulou

“…A comparison of four loss functions—Mean Square Error (MSE), Huber, Asymmetric Mean Squared Error (AMSE), and Quantile Loss—revealed that MSE offered balanced performance, Huber Loss achieved the highest reduction in systematic RMSE, and AMSE performed best in peak detection. Additionally, four deep learning architectures were evaluated: baseline CNN-LSTM, a hybrid model with attention mechanisms, a transformer-based model, and an End-to-End framework. …”
Get full text

QPPLab: A generally applicable software package for detecting, analyzing, and visualizing large-scale quasiperiodic spatiotemporal patterns (QPPs) of brain activity by Nan Xu, Behnaz Yousefi, Nmachi Anumba, Theodore J. LaGrow, Xiaodi Zhang, Shella Keilholz

“…Quasi-periodic patterns (QPPs) are prominent spatiotemporal brain dynamics observed in functional neuroimaging data, reflecting the alternation of high and low activity across brain regions and their propagation along cortical gradients. …”
Get full text

Uncovering abnormal gray and white matter connectivity patterns in Alzheimer’s disease spectrum: a dynamic graph theory analysis for early detection by Juanjuan Jiang, Tao Kang, Ronghua Ling, Yingqian Liu, Jiuai Sun, Yiming Li, Xiaoou Li, Hui Yang, Bingcang Huang, the Alzheimer’s Disease Neuroimaging Initiative

Get full text

Automatic Detection of Landslide Surface Cracks from UAV Images Using Improved U-Network by Hao Xu, Li Wang, Bao Shu, Qin Zhang, Xinrui Li

“…Surface cracks are key indicators of landslide deformation, crucial for early landslide identification and deformation pattern analysis. However, due to the complex terrain and landslide extent, manual surveys or traditional digital image processing often face challenges with efficiency, precision, and interference susceptibility in detecting these cracks. …”
Get full text

MT-CMVAD: A Multi-Modal Transformer Framework for Cross-Modal Video Anomaly Detection by Hantao Ding, Shengfeng Lou, Hairong Ye, Yanbing Chen

“…Video anomaly detection (VAD) faces significant challenges in multimodal semantic alignment and long-term temporal modeling within open surveillance scenarios. …”
Get full text

Transfer learning based deep architecture for lung cancer classification using CT image with pattern and entropy based feature set by Nithya R, Vidhyapathi C.M

“…Abstract Early detection of lung cancer, which remains one of the leading causes of death worldwide, is important for improved prognosis, and CT scanning is an important diagnostic modality. …”
Get full text

A hybrid deep learning-based intrusion detection system for EV and UAV charging stations by Rosebell Paul, Mercy Paul Selvan

“…The SS-ADRNN model incorporates squirrel search optimization, which is inspired by the foraging behaviour of squirrels, to dynamically adjust charging station operations based on environmental conditions and demand patterns. Additionally, attention mechanisms are employed to prioritize relevant input features, enabling the model to focus on critical information during decision-making processes. …”
Get full text