Motion (change) detection is a basic preprocessing step in video processing, which has many application scenarios. One challenge that deep learning-based methods require high computation power to improve their accuracy. In this paper, we introduce novel semantic segmentation and lightweight-based network for motion detection, called Real-time Detection Network Based on Single Linear Bottleneck ...

The problem of Dynamic Job Shop (DJS) scheduling is one of the most complex problems of machine scheduling. This problem is one of NP-Hard problems for solving which numerous heuristic and metaheuristic methods have so far been presented. Genetic Algorithms (GA) are one of these methods which are successfully applied to these problems. In these approaches, of course, better quality of solutions...

Active Queue Management (AQM) plays an important role in the Internet congestion control. It tries to enhance congestion control, and to achieve tradeoff between bottleneck utilization and delay. Random Early Detection (RED) is the most popular active queue management algorithm that has been implemented in the in Internet routers and is trying to supply low delay and low packet loss. RED al...

In this paper, we utilize deep learning to learn high-level features for audio chord detection. The learned features, obtained by a deep network in bottleneck architecture, give promising results and outperform state-of-the-art systems. We present and evaluate the results for various methods and configurations, including input pre-processing, a bottleneck architecture, and SVMs vs. HMMs for cho...

active queue management (aqm) plays an important role in the internet congestion control. it tries to enhance congestion control, and to achieve tradeoff between bottleneck utilization and delay. random early detection (red) is the most popular active queue management algorithm that has been implemented in the in internet routers and is trying to supply low delay and low packet loss. red algori...

Object detection in aerial images is a critical and essential task the fields of geoscience remote sensing. Despite popularity computer vision methods detecting objects, these have been faced with significant limitations such as appearance occlusion variable object sizes. In this letter, we explore conventional neck networks by analyzing information bottlenecks. We propose an enhanced network t...