Manually processing documents is time consuming, expensive and prone to error. The growing number of file formats and manual inputs opens up the way for a new generation of AI Models that can extract information from complex document types such as contracts, tax documents, invoices, legal contracts, insurance and healthcare claims.
Forged Art Detection
Defining the authenticity of a work of art has long been a considerable challenge. The astute eye of art appraisers is key to deal with the increased number of duplicated art. Combined with AI, evaluating the authenticity of an art piece can become affordable, time efficient and accurate.
There are limitless types of plants and weeds. Their identification and classification is time and resource consuming but crucial for botanists. Deep learning models can help with the execution of this hectic task with ease and enrich the study field of plants.
Patterns and textures can hardly be identified in images and videos. Deep learning based techniques are competent enough to categorize and identify texture and patterns in images. It identifies typical textures (feathers, woodgrain), unique/new notions (petrified wood, glacial ice), and broad descriptive concepts (veined, metallic).
Birds are amongst the most diverse species of vertebrates. Their classification can be challenging for ornithologists. With the contribution of AI, it becomes easy to monitor bird populations. Our deep learning model based on image classification is able to identify and accurately classify a plethora of birds.
Sorting produce is a lenghthy process to conduct manually. The use of deep learning models can help to automatically sort out fruits and vegetables which are unsuitable to market or storage due to mechanical damages, insects or diseases.
Hate symbols are a serious problem affecting media platforms. Their ban on media is critical to ensure a safe and inclusive environment for everyone. Deep learning models can detect photos and videos that contain insensitive hateful symbols that discriminate against people and immediatley flag them.