Deep learning is a process that is closely coupled to machine learning. In Deep learning, artificial neural networks, human brain-inspired algorithms learn from large amounts of data. It is similar in nature to how we learn from past experience. The deep learning algorithm helps the system understanding variety of inputs to improve the result of the algorithm.
Deep learning enables machines or devices to overcome practical problems. For instance, in a detecting a face with single person in view is different from detecting them in crowd. The more deep and profound examples they learn, the better are the results. In fact, Deep Learning is a key mechanism in several detection mechanisms like age detections, sign detection, color detection and others
Challenges we have solved till today
Object Detection from Video & Image
In deep learning, the concept object detection is the method of getting real-world objects form images or videos and understand them. These objects can be specs, vehicles, traffic signals, houses or even buildings. With Deep Learning, you assist your machine in getting smarter in recognising and pinpointing your outcome. For instance, in a snacks manufacturing plant, there can be multiple types of defects in a product like a burnt snack, a bad ingredient, a different shape of snack item or a crushed piece of item. Such scenarios can be detected easily when the line is running slowly and there are less items to evaluate. With Deep learning, we speed up this detection process and help the machine get trained to process faster.
Face Detection and Facial Expression
Face Detection and Facial expression recognition system is a technology that detects emotions and feelings in human faces using biometric patterns. Much more exactly, this innovation is a sentiment analysis method and can detect six fundamental or universal expressions automatically i.e. happiness/joy, sadness/sorrow, anger, surprise, fear, and disgust. With a variety of faces existing in the world, applying deep learning on facial detection algorithms becomes very important. This is done by evaluating faces from varying regions using live video feed, past videos, and images available for training.
In Deep learning, speech recognition is the capability of a machine or program to classify and transform phrases and words into a device - readable format in the spoken language. Talking about one of most exciting innovations in the research and development laboratory of Baidu is what the company dubs Deep Voice. Deep Voice is a technology which can create naturally occurring human voices. These voices are quite hard to distinguish from real human speech. This is made possible by taking in variety of voices and understanding how to generate them. We help you by obtaining as well as providing a detailed dataset of voices and training data.
In a world with over 6500 languages, training the algorithms manually for every language would be extremely difficult. The normal process of building a language translation algorithm is to create some basic building blocks to translate simple statements. This algorithm is then trained over more complex statements and outputs are matched to train further. This entire process takes place on the go on a device or system. Deep Learning in language translation allows the system to pick up local nuances of every desired language with the large amount of data available for ingestion. We are always hunting for new challenges in every field to work with. If you have a challenge, we certainly have a team to help you solve it.