To ensure good performance, modern machine learning models typically require large
amounts of quality annotated data. Meanwhile, the data collection and annotation processes …

Deep learning algorithms have exhibited impressive performance across various computer
vision tasks; however, the challenge of overfitting persists, especially when dealing with …

The performance of existing supervised neuron segmentation methods is highly dependent
on the number of accurate annotations, especially when applied to large scale electron …

In recent years, YOLO object detection models have undergone significant advancement
due to the success of novel deep convolutional networks. The success of these YOLO …

Abstract We present You Only Cut Once (YOCO) for performing data augmentations. YOCO
cuts one image into two pieces and performs data augmentations individually within each …

In recent years, one of the most popular techniques in the computer vision community has
been the deep learning technique. As a data-driven technique, deep model requires …

This paper addresses data augmentation for action segmentation. Our key novelty is that we
augment the original training videos in the deep feature space, not in the visual …

Modern approach to artificial intelligence (AI) aims to design algorithms that learn directly
from data. This approach has achieved impressive results and has contributed significantly …

Multi-agent Reinforcement Learning (MARL) has gained wide attention in recent years and
has made progress in various fields. Specifically, cooperative MARL focuses on training a …

Object detection is a fundamental task in computer vision that aims to locate and classify
objects in images or videos. The one-stage You Only Look Once (YOLO) models are …