Pests and diseases pose a key challenge to passion fruit farmers across Uganda and East Africa in general. They lead to loss of investment as yields reduce and losses increases. As the majority of the farmers, including passion fruit farmers, in the country are smallholder farmers from low-income households, they do not have the sufficient information and means to combat these challenges. While, passion fruits have the potential to improve the well-being of these farmers as they have a short maturity period and high market value, without the required knowledge about the health of their crops, farmers cannot intervene promptly to turn the situation around. For this work, we have partnered with the Uganda National Crop Research Institute (NaCRRI) to develop a dataset of expertly labelled passion fruit plant leaves and fruits, both diseased and healthy.

Absolute Reports is an upscale platform to help key personnel in the business world in strategizing and taking visionary decisions based on facts and figures derived from in depth market research. We are one of the top report resellers in the market, dedicated towards bringing you an ingenious concoction of data parameters.

COVID-19 Outbreak-Global Artificial Intelligence (AI) in Healthcare Industry Market Report-Development Trends, Threats, Opportunities and Competitive Landscape in 2020 is latest research study released by HTF MI evaluating the market, highlighting opportunities, risk side analysis, and leveraged with strategic and tactical decision-making support. The study provides information on market trends and development, drivers, capacities, technologies, and on the changing investment structure of the COVID-19 Outbreak-Global Artificial Intelligence (AI) in Healthcare Market. Some of the key players profiled in the study are Zephyr Health, Inc., Atomwise, Inc, Enlitic, Inc., Nvidia Corporation, Welltok, Inc., General Vision, Inc., Microsoft Corporation, Sentirian, IBM Corporation, Next IT Corporation, Intel Corporation, Google Inc. & Siemens Healthineers GmbH. If you are involved in the COVID-19 Outbreak- Artificial Intelligence (AI) in Healthcare industry or intend to be, then this study will provide you comprehensive outlook. It's vital you keep your market knowledge up to date segmented by Patient Data and Risk Analysis, Medical Imaging and Diagnosis, Lifestyle Management and Monitoring, Virtual Assistant, Precision Medicine, In-Patient Care and Hospital Management, Drug Discovery, Wearables & Research,, Deep Learning, Querying Method, NLP & Context Aware Processing and major players.

Natural Language Processing is considered one of the many critical aspects of making intelligent systems. By training your solution with data gathered from the real-world, you can make it faster and more relevant to users, generating crucial insight about your customer base. In this article, we will be taking a look at how Python offers some of the most useful and powerful libraries for leveraging the power of Natural Language Processing into your project and where exactly do they fit in. Often recognized as a professional-grade Python library for advanced Natural Language Processing, spaCy excels at working with incredibly large-scale information extraction tasks. Built using Python and Cython, spaCy combines the best of both languages, the convenience from Python and the speed from Cython to deliver one of the best-in-class NLP experiences. Stanford CoreNLP is a suite of tools built for implementing a Natural Language Processing into your project.

In March of 2015, protests broke out at the University of Cape Town in South Africa over the campus statue of British colonialist Cecil Rhodes. Rhodes, a mining magnate who had gifted the land on which the university was built, had committed genocide against Africans and laid the foundations for apartheid. Under the rallying banner of "Rhodes Must Fall," students demanded that the statue be removed. Their protests sparked a global movement to eradicate the colonial legacies that endure in education. The events also provoked Shakir Mohamed, a South African AI researcher at DeepMind, to reflect on what colonial legacies might exist in his research as well.

Elon Musk thinks his company Tesla will have fully autonomous cars ready by the end of 2020. "There are no fundamental challenges remaining," he said recently. "There are many small problems. While the technology to enable a car to complete a journey without human input (what the industry calls "level 5 autonomy") might be advancing rapidly, producing a vehicle that can do so safely and legally is another matter. Read more: Are self-driving cars safe?

New research demonstrates for the first time that artificial intelligence (AI) can be used to train computers to recognize individual birds, a task humans are unable to do. The research is published in the British Ecological Society journal Methods in Ecology and Evolution. "We show that computers can consistently recognize dozens of individual birds, even though we cannot ourselves tell these individuals apart. In doing so, our study provides the means of overcoming one of the greatest limitations in the study of wild birds--reliably recognizing individuals." Said Dr. André Ferreira at the Center for Functional and Evolutionary Ecology (CEFE), France, and lead author of the study.

No matter what industry you operate in, you'll have noticed by now that technology is changing the way we do business. Technology continues to evolve, and businesses need to keep up or risk becoming obsolete. Companies that continue to practice traditional business methods will find it more difficult to stay relevant and competitive. If they overlook the significance of digital transformation, they face an imminent threat of being outsmarted by more innovative players in the game. The day is coming when digital transformation will mean the difference between survival, and the ability to thrive in this technology-driven world.

Southern Africa has experienced drought-flood cycles for the past decade that strain the ability of any country to properly manage water resources. This dynamic is exacerbated by human drivers such as the heavy reliance of sectors such as mining and agriculture on groundwater and surface water, as well as subsistence agriculture in rural areas along rivers. These factors have progressively depleted natural freshwater systems and contributed to an accumulation of sediment in river systems. In a region where two or more countries share many of the groundwater and surface resources, water security cuts across the socioeconomic divide and is both a rural and urban issue. For example, the City of Cape Town had to heavily ration all water uses in 2017 and 2018, as its dams were drying up.

Tactician helps users make tactical proof decisions while they retain control over the general proof strategy. To this end, Tactician learns from previously written tactic scripts and gives users either suggestions about the next tactic to be executed or altogether takes over the burden of proof synthesis. Tactician's goal is to provide users with a seamless, interactive, and intuitive experience together with robust and adaptive proof automation. In this paper, we give an overview of Tactician from the user's point of view, regarding both day-to-day usage and issues of package dependency management while learning in the large. Finally, we give a peek into Tactician's implementation as a Coq plugin and machine learning platform.