The symbolic AI paradigm of the 1970s led to the development of rule-based, expert systems. Soon, one early implementation was the MY-CIN system in the medical field. Parallel to these developments, ML and AI algorithms moved from heuristics-based techniques to manual,handcrafted feature extraction techniques and then to supervised learning techniques. ML started the sparks, particularly in deep learning, a branch of ML that employs multi-layered neural networks. No sooner, deep learning started doing well in image classification and processing tasks, mainly owing to convolutional neural networks(CNN)and spiked neural networks(SNN). Their use became popularized from the availability of large labelled data sets being available,hardware advancements in Graphical Processing Units(GPUs)that led to improvements in CNN performance, and their widespread use in image detection. The widespread use of CNNs in image recognition came about after Krizhevsky, who won the 2012 Imagenet Large Scale Visual Recognition Challenge(ILSVRC) with a CNN that had a 15 percent error rate. The runner up had almost doubled the error rate at 26 percent. Thereafter, CNNs have become the dominant architecture in image analysis in core fields of medical, pharma, security, and other technological fields. In the Indian landscape,a technology driven organization, New Delhi headquartered, ASADEL Technologies, has been

redesigning and reinterpreting the analytical systems using these
watershed technologies. ASADELTECH, with ML and AI-enabled systems, has further enhanced capabilities of unstructured data of client companies with unconventional and innovative solutions and applications. landscape, a technology driven organization, New Delhi headquartered, ASADEL Technologies, has been redesigning and reinterpreting the analytical systems using these watershed technologies. ASADELTECH, with ML and AI-enabled systems, has further enhanced capabilities of unstructured data of client companies with unconventional and innovative solutions and applications.

"ASADELTECH, In Its feat to redefine medical detection through image analytics,is actively automating teaching and building up the competency level of their solution"

Being an analytic organization at the core, it caters to specific industrial and enterprise needs. The primary areas being focused currently include faster automated primary level of diagnostics in medical/healthcare sector, better capacity & productivity planning in private sectors and governmental organizations. The company provides an entire landscape of state-of-the-art image and video analytics that are uniquely suited for detection of medical conditions, time & motion study in the transport & retail industries, face recognition and forensic support.

Simplifying lives by decoding information stored in every pixel ASADELTECH focuses on more specific, often perpetual tasks. Extending the literal meaning of Deep Learning in Image Analytics, the company teaches the systems to recognize objects that are important, without humans' instruction or involvement.In one such product,the company has fitted this explanation in the Smart City environment,where their comprehensive command & control centre solution

is ergonomically designed to streamline and interface technology with operations for smart monitoring of safety and well-being of citizens. Further, it augments the rendering of security with high precision face recognition kits. The face recognition module has been delivering high accuracy levels in adverse conditions such as those in coal mines.

Moreover, ASADELTECH brings in an unprecedented sensitivity in telling the difference between various objects or different features in an image, mainly useful in medical field. Medical images are typically volumetric images(3D)and sometimes have an additional time dimension (4D)or multiple channels. Using in-house developed deep learning architecture the company now extracts and encodes detailed information from both spatial and spectral dimensions. Its super resolution algorithms aim to learn howto reconstruct high-resolution images from sampling low resolution inputs. These high-resolution images are then used to identify medical conditions and screens for malignancy of the underlying diseases like cancer, tuberculosis and other chronic ailments with the help of its proprietary NN models. ASADELTECH, in its feat to redefine medical detection through imageanalytics, is actively automating, teaching and building up the competency level of their solution.

With a promising future ahead for image analytics,the company has elaborate product strategies for the full life-cycle of all its products and solutions. As such, what stared its journey in the 1970s with MYCIN, soon grew into Deep Learning CNNs scoring checkpoints in several fields. And now,companies like ASADEL Technologies are all set to propel its extensive research in technology into world class, highly efficient and robust products that would transform the way video & image analytics are being used by corporate,enterprises and healthcare organizations.