Toxicity prediction is a critical step in the drug discovery process that helps identify and
prioritize compounds with the greatest potential for safe and effective use in humans, while …

Leveraging datasets available to learn a model with high generalization ability to unseen
domains is important for computer vision, especially when the unseen domain's annotated …

Traditionally, speech emotion recognition (SER) research has relied on manually
handcrafted acoustic features using feature engineering. However, the design of …

Semantic segmentation is a promising machine learning (ML) method for highly precise fine-
scale defect detection and part qualification in additive manufacturing (AM). Most existing …

Training and testing process for the classification of biomedical datasets in machine learning
is very important. The researcher should choose carefully the methods that should be used …

Thermodynamic properties of complex systems play an essential role in developing
chemical engineering processes. It remains a challenge to predict the thermodynamic …

Diabetes mellitus (DM) is one of the deadliest diseases in the world, especially in developed
nations. In recent years, it has become rampant in the developing nations such as Nigeria …

Mood inference with mobile sensing data has been studied in ubicomp literature over the
last decade. This inference enables context-aware and personalized user experiences in …

Highlights•Designed an end-to-end vision system for a mango picking robot.•Instance
segmentation and pick point detection are performed simultaneously.•It is robust to various …

Federated Learning (FL) is a distributed machine learning technique, where each device
contributes to the learning model by independently computing the gradient based on its …