IEEE

Causality-Inspired Debiasing Learning for Open World Object Detection

Abstract: Open world object detection (OWOD) aims to identify both known instances of trained classes and unknown ones. Despite recent advancements, existing methods exhibit a detection bias towards ...
IEEE

DFFormer: UAV Object Detection via Feature Scaling and Interaction

Abstract: Machine vision-based anti-drone detection systems enable long-range, cost-effective target monitoring in complex environments. However, small drones typically occupy only a few pixels in ...
GitHub

One command to explain your Python environment, trace imports, and detect shadows.

Note: uvx pywho is not recommended — it runs inside uv's ephemeral sandbox, so the output reflects that temporary environment instead of your actual project. Always install pywho into the environment ...
IEEE

Attention-based CNN-BiLSTM Model With CTGAN Sample Augmentation for Intrusion Detection in IoT

Abstract: Intrusions or attacks on IoT networks have dramatically increased in recent years. As a result, protecting IoT infrastructure from these threats became essential to its global acceptance.
IEEE

A Novel Approach to Deepfake Detection: Leveraging Fused Facial and Body Dynamics With a CNN–Transformer Hybrid Network

Abstract: The rapid advancement of generative models like Generative Adversarial Networks (GANs) has contributed significantly to the creation of deep-fake videos. These synthetic videos pose serious ...
IEEE

Efficient Test-Time Adaptive Object Detection via Sensitivity-Guided Pruning

Abstract: Continual test-time adaptive object detection (CTTA-OD) aims to online adapt a source pre-trained detector to everchanging environments during inference under continuous domain shifts. Most ...
IEEE

Hierarchical Spatiotemporal Fusion for Event-Visible Object Detection

Abstract: Traditional visible light cameras are prone to performance degradation under varying weather and lighting conditions. To address this challenge, we introduce an eventbased camera and propose ...
IEEE

Optimizing Accuracy and Efficiency in Brain Tumor Detection: CNN with Moth Flame Optimization vs. EfficientNet V2-B20

Abstract: The identification of brain tumors using the Magnetic Resonance Imaging (MRI) is an essential operation in medical diagnostics, whose early and precise detection can greatly influence the ...
IEEE

MDSF-YOLO: Advancing Object Detection With a Multiscale Dilated Sequence Fusion Network

Abstract: Accurate and fast detection of traffic signs is critical for autonomous driving, particularly in complex environments with diverse sign scales and varying detection distances. Existing ...
IEEE

MonoGSDet: Monocular 3D Object Detection With Gaussian Splatting in Autonomous Driving

Abstract: Monocular 3D object detection has gained considerable attention because of its cost-effectiveness and practical applicability, particularly in autonomous driving and robotics. Most of ...
IEEE

EFAF-YOLO: A Novel Enhanced Framework for Small-Object Detection

Abstract: Remote sensing platforms provide crucial data for applications such as urban planning and traffic monitoring. However, detecting small objects remains challenging due to low resolution, ...
IEEE

Accurate Fake News Detection in Text-Based Content Using K-Nearest Neighbor, LSTM, MLP and CNN Models

Abstract: With the proliferation of social media platforms, where users are free to express themselves and share content, the detection of fake news in text has become an important issue. The ...