Related papers: Farmer's Assistant: A Machine Learning Based Appli…
Diseases and pests cause huge economic loss to the apple industry every year. The identification of various apple diseases is challenging for the farmers as the symptoms produced by different diseases may be very similar, and may be present…
Artificial Intelligence is everywhere today. But unfortunately, Agriculture has not been able to get that much attention from Artificial Intelligence (AI). A lack of automation persists in the agriculture industry. For over many years,…
An accurate and timely detection of diseases and pests in rice plants can help farmers in applying timely treatment on the plants and thereby can reduce the economic losses substantially. Recent developments in deep learning based…
Leaf disease is a common fatal disease for plants. Early diagnosis and detection is necessary in order to improve the prognosis of leaf diseases affecting plant. For predicting leaf disease, several automated systems have already been…
Inclusion of high throughput technologies in the field of biology has generated massive amounts of biological data in the recent years. Now, transforming these huge volumes of data into knowledge is the primary challenge in computational…
Insect pests continue to bring a serious threat to crop yields around the world, and traditional methods for monitoring them are often slow, manual, and difficult to scale. In recent years, deep learning has emerged as a powerful solution,…
Artificial Intelligence (AI) and its data-centric branch of machine learning (ML) have greatly evolved over the last few decades. However, as AI is used increasingly in real world use cases, the importance of the interpretability of and…
India's agricultural system has been facing a severe problem of crop wastage. A key contributing factor to this problem is that many small farmers lack access to reliable cold storage that extends crop shelf-life. To avoid having leftover…
Accurate crop disease diagnosis is essential for sustainable agriculture and global food security. Existing methods, which primarily rely on unimodal models such as image-based classifiers and object detectors, are limited in their ability…
India loses 35% of the annual crop yield due to plant diseases. Early detection of plant diseases remains difficult due to the lack of lab infrastructure and expertise. In this paper, we explore the possibility of computer vision approaches…
Human society needs to increase food production by an estimated 70% by 2050 to feed an expected population size that is predicted to be over 9 billion people. Currently, infectious diseases reduce the potential yield by an average of 40%…
Crop diseases are a major threat to food security and their rapid identification is important to prevent yield loss. Swift identification of these diseases are difficult due to the lack of necessary infrastructure. Recent advances in…
The number of people living in this agricultural nation of ours, which is surrounded by lush greenery, is growing on a daily basis. As a result of this, the level of arable land is decreasing, as well as residential houses and industrial…
Agricultural research has been profited by technical advances such as automation, data mining. Today, data mining is used in a vast areas and many off-the-shelf data mining system products and domain specific data mining application soft…
Agricultural research is essential for increasing food production to meet the requirements of an increasing population in the coming decades. Recently, satellite technology has been improving rapidly and deep learning has seen much success…
India generates substantial volumes of public agricultural data, yet artificial intelligence (AI) adoption in farming remains limited and largely confined to pilot initiatives. This paper examines this gap by assessing India's agricultural…
The preservation of soil health is a critical challenge in the 21st century due to its significant impact on agriculture, human health, and biodiversity. We provide the first deep investigation of the predictive potential of machine…
Jamun leaf diseases pose a significant threat to agricultural productivity, negatively impacting both yield and quality in the jamun industry. The advent of machine learning has opened up new avenues for tackling these diseases effectively.…
Manual observation and monitoring of individual cows for disease detection present significant challenges in large-scale farming operations, as the process is labor-intensive, time-consuming, and prone to reduced accuracy. The reliance on…
The potato is a widely grown crop in many regions of the world. In recent decades, potato farming has gained incredible traction in the world. Potatoes are susceptible to several illnesses that stunt their development. This plant seems to…