The manual prediction of plant species and plant diseases is expensive, time-consuming,
and requires expertise that is not always available. Automated approaches, including …

基于多任务神经网络模型, 提出一种多任务测井储层参数预测方法, 利用测井数据对储层孔隙度,
渗透率及含水饱和度同时进行预测. 分别采用同架构和异架构多任务模型对测井储层参数进行 …

With the emergence of varied visual navigation tasks (eg, image-/object-/audio-goal and
vision-language navigation) that specify the target in different ways, the community has …

Endgame studies have long served as a tool for testing human creativity and intelligence.
We find that they can serve as a tool for testing machine ability as well. Two of the leading …

Due to the complicated background and noise of infrared images, infrared small target
detection is one of the most difficult problems in the field of computer vision. In most existing …

Despite the fast progress of explanation techniques in modern Deep Neural Networks
(DNNs) where the main focus is handling" how to generate the explanations", advanced …

The research on driver fatigue detection is of great significance to improve driving safety.
This paper proposes a real-time comprehensive driver fatigue detection algorithm based on …

Assigning developers and allocating issue types are two important tasks in the bug triage
process. Existing approaches tackle these two tasks separately, which is time-consuming …

Studying automated rail surface defect detection methods instead of manual inspections can
not only save time and cost, but also increase the safety of railway transport. Consequently …

Despite the recent progress in speech emotion recognition (SER), state-of-the-art systems
lack generalisation across different conditions. A key underlying reason for poor …