These sources contain images that viewers would have to interpret themselves. Most images do not have a description, but the human can largely understand them without their detailed captions. However, machine needs to interpret some form of image captions if humans need automatic image captions from it. Image captioning is important for many reasons. For example, they can be used for automatic image indexing. Image indexing is important for Content-Based Image Retrieval (CBIR) and therefore, it can be applied to many areas, including biomedicine, commerce, the military, education, digital libraries, and web searching. Social media platforms such as Facebook and Twitter can directly generate descriptions from images. The descriptions can include where we are (e.g., beach, cafe), what we wear and importantly what we are doing there.

Abstract-- Dexterous multi-fingered robotic hands can perform a wide range of manipulation skills, making them an appealing component for general-purpose robotic manipulators. However, such hands pose a major challenge for autonomous control, due to the high dimensionality of their configuration space and complex intermittent contact interactions. In this work, we propose deep reinforcement learning (deep RL) as a scalable solution for learning complex, contact rich behaviors with multi-fingered hands. Deep RL provides an end-to-end approach to directly map sensor readings to actions, without the need for task specific models or policy classes. We show that contact-rich manipulation behavior with multi-fingered hands can be learned by directly training with model-free deep RL algorithms in the real world, with minimal additional assumption and without the aid of simulation. We learn a variety of complex behaviors on two different low-cost hardware platforms. We show that each task can be learned entirely from scratch, and further study how the learning process can be further accelerated by using a small number of human demonstrations to bootstrap learning. Our experiments demonstrate that complex multi-fingered manipulation skills can be learned in the real world in about 4-7 hours for most tasks, and that demonstrations can decrease this to 2-3 hours, indicating that direct deep RL training in the real world is a viable and practical alternative to simulation and model-based control.

The abundance of overlapping anatomical structures appearing in chest radiographs can reduce the performance of lung pathology detection by automated algorithms (CAD) as well as the human reader. In this paper, we present a deep learning based image processing technique for enhancing the contrast of soft lung structures in chest radiographs using Fully Convolutional Neural Networks (FCNN). Two 2D FCNN architectures were trained to accomplish the task: The first performs 2D lung segmentation which is used for normalization of the lung area. The second FCNN is trained to extract lung structures. To create the training images, we employed Simulated X-Ray or Digitally Reconstructed Radiographs (DRR) derived from 516 scans belonging to the LIDC-IDRI dataset. By first segmenting the lungs in the CT domain, we are able to create a dataset of 2D lung masks to be used for training the segmentation FCNN. For training the extraction FCNN, we create DRR images of only voxels belonging to the 3D lung segmentation which we call "Lung X-ray" and use them as target images. Once the lung structures are extracted, the original image can be enhanced by fusing the original input x-ray and the synthesized "Lung X-ray". We show that our enhancement technique is applicable to real x-ray data, and display our results on the recently released NIH Chest X-Ray-14 dataset. We see promising results when training a DenseNet-121 based architecture to work directly on the lung enhanced X-ray images.

The Indian Railway Catering and Tourism Corporation Limited (IRCTC) Saturday launched'AskDisha' (Digital Interaction to Seek Help Anytime) -- a chatbot powered by artificial intelligence (AI) for improving customer services of railway passengers, a statement from railways said. A chatbot is a special computer programme designed to simulate conversation with users, especially over the internet. "The IRCTC Chat Bot AskDisha will offer greatly improved and intuitive customer support by answering customer queries pertaining to all aspects of the services that IRCTC provides. It will support several regional languages and will be voice-enabled and will soon be integrated with the IRCTC android app," the statement said. The essential features of AskDisha include ability to quickly answer to customer queries, ability to multitask, ability to provide round-the-clock customer support, zero waiting time for the query to get answered and overall an ability to provide customer with a stress-free experience and overall customer satisfaction, it said.

Countries like America and China are leading the front in AI technology. However, many are still concerned at the thought of robots replacing us and the social stigma attached with the integration of AI in the legal industry. To better that understanding, we've decided to interview Dr Richard Cornes from the University of Essex, a constitutional lawyer and a psychoanalyst. In short, he's the perfect person to question the legitimacy of AI in the legal industry. "Psycho-analysis is described as the matrix of looking at the way things are and say why they're doing what they are doing. Now, I run the module on Understanding Judges at the University of Essex which primarily focus on my area of research: psycho-analysis to understand how judges think and how the law works."

How do you have to distort a face so that facial recognition algorithms no longer see a face–and evade the technology that has become so pervasive in our world? That was the question the Seoul-based artistic duo Shin Seung Back and Kim Yong Hun posed to a group of 10 different painters. The result is their series Nonfacial Portrait, a striking collection of painted portraits that evade the algorithms. The paintings, which are currently on display at the Seoul Museum of Art, are each so wildly different that you wouldn't know they were all inspired by a single photo of Yong Hun. One has a sky blue outline of a bust, with the eyes, mouth, and nose scattered around the canvas.

Dubai: Artificial Intelligence-powered services, such as customer call management system and drone-based statistician, will be showcased at Smart Dubai's pavilion of 59 government and private establishments at the GITEX Technology Week 2018, which begins on Sunday. Running till Thursday at Dubai World Trade Centre, GITEX will feature the establishments exhibiting their latest smart services to the public. Dr Aisha Bint Butti Bin Bishr, director general of Smart Dubai Office, said: "Since its inception, Smart Dubai has been on a mission to implement the vision of His Highness Shaikh Mohammad Bin Rashid Al Maktoum, Vice-President and Prime Minister of the UAE and Ruler of Dubai, to transform Dubai into a full-fledged smart city and make it one of the happiest in the world. His Highness has also called on all stakeholders across the public and private sectors to work together and strive towards that ambitious objective. We at Smart Dubai have forged numerous partnerships as we progress towards our goals, and are delighted that these partners – be they government entities, private organisations, or start-ups – are joining us [at GITEX] to showcase their advanced smart services created for the people and the community."

Shanghai: By 2025, the global Artificial Intelligence (AI) market is expected to reach $380 billion, 90 per cent of which will come from the enterprise market, a Huawei official said here. "Naturally, we believe that industry applications will be key to the success of AI over the next decade," William Xu, Director of the Board and Chief Strategy Marketing Officer, said in his keynote address on the second day of the Huawei Connect 2018. He said that Huawei plans to support one million AI developers and partners over three years. "Helping industries go digital is not something that any company can do on its own. To effectively go digital, industries and industry organizations need to work together," he said.

At the International Conference on Intelligent Robots and Systems (IROS) held in Madrid earlier this month, researchers presented a flexible snake-like robot that is able to climb ladders. The project was a collaboration between Kyoto University and the University of Electro-Communications in Japan. A newly developed gait allows the robot snake to bend and twist its smooth body to create a series of connected shapes, which slowly but securely wrap around each rung as it climbs upwards. This breakthrough could be helpful in disaster recovery situations – enabling rescuers to access damaged buildings and other infrastructure more easily, navigating obstacles or terrain that even human-like robots might have trouble with. The snake is able to climb ladders that are both inclined and fully vertical.

You may not think the number of words in an email subject line says anything about you, but at least one company is betting that the metric can help determine your likelihood of paying back a loan. LenddoEFL, based in Singapore, is one of a handful of startups using alternative data points for credit scoring. Those companies review behavioral traits and smartphone habits to build models of creditworthiness for consumers in emerging markets, where standard credit reporting barely exists. In addition to analyzing financial-transaction data, Lenddo's algorithm takes into consideration things such as whether you avoid one-word subject lines (meaning you care about details) and regularly use financial apps on your smartphone (meaning you take your finances seriously). Lenddo also looks at the ratio of smartphone photos in your library that were taken with a front-facing camera, since selfies indicate youth, helping the company divide people into customer segments.