Agricultural losses due to post-harvest diseases can reach up to 30% of total production.
Detecting diseases in fruits at an early stage is crucial to mitigate losses and ensure the …

The purpose of this research is to propose a novel framework called “MNet: Merged Net” for
fast and accurate fruit classification, which addresses the misclassification problem …

Handwriting Recognition has been a field of great interest in the Artificial Intelligence
domain. Due to its broad use cases in real life, research has been conducted widely on it …

To ensure proper knowledge representation of the kitchen environment, it is vital for kitchen
robots to recognize the states of the food items that are being cooked. Although the domain …

Correct identification and categorization of plant diseases are crucial for ensuring the safety
of the global food supply and the overall financial success of stakeholders. In this regard, a …

Accurate identification and classification of plant diseases play a vital role in safeguarding
global food production and ensuring the economic well-being of the stakeholders. Various …

In public health surveillance, the identification of Personal Health Mentions (PHM) is an
essential initial step. It involves examining a social media post that mentions an illness and …

Deep Learning (DL) has recently emerged as a pivotal tool in a wide variety of agricultural
end-level applications. While promising outcomes have been achieved in crop disease …

Potato cultivation faces significant harvest loss from several diseases, emphasizing the
importance of early and accurate disease detection. Analyzing potato leaf images using …

Fungal species classification is an important task with broad implications for medicine,
agriculture, and ecology. Even though they work well, traditional identification techniques …